Background: Although healthy lifestyle has been linked with a reduced risk of cardiovascular diseases (CVDs), the potential metabolic mechanism underlying this association remains unknown. Methods: We included 161,018 CVD-free participants from the UK Biobank. Elastic net regression was utilized to generate a healthy lifestyle-related metabolic signature. The Cox proportional hazards model was applied to investigate associations of lifestyle-related metabolic signature with incident CVDs, and mediation analysis was conducted to evaluate the potential mediating role of metabolic profile on the healthy lifestyle-CVD association. Mendelian randomization (MR) analysis was conducted to detect the causality. Results: During 13 years of follow-up, 17,030 participants developed incident CVDs. A healthy lifestyle-related metabolic signature comprising 123 metabolites was established, and it was inversely associated with CVDs. The hazard ratio (HR) was 0.83 (95% confidence interval [CI]: 0.81, 0.84) for CVD, 0.83 (95% CI: 0.81, 0.84) for ischemic heart disease (IHD), 0.86 (95% CI: 0.83, 0.90) for stroke, 0.86 (95% CI: 0.82, 0.89) for myocardial infarction (MI), and 0.75 (95% CI: 0.72, 0.77) for heart failure (HF) per standard deviation increase in the metabolic signature. The metabolic signature accounted for 20% of the association between healthy lifestyle score and CVD. Moreover, MR showed a potential causal association between the metabolic signature and stroke. Conclusions: Our study revealed a potential link between a healthy lifestyle, metabolic signatures, and CVD. This connection suggests that identifying an individual’s metabolic status and implementing lifestyle modifications may provide novel insights into the prevention of CVD.

Objective: To investigate the effect of Enterovirus A71 (EV71) vaccination on the transmissibility of different enterovirus serotypes of hand, foot, and mouth disease (HFMD) in Zhejiang, China. Methods: Daily surveillance data of HFMD and EV71 vaccination from August 2016 to December 2019 were collected. Epidemic periods for each HFMD type were defined, and the time-varying effective reproduction number (R_t) was estimated, which could provide more direct evidence of disease epidemics than case number. General additive models (GAMs) were employed to analyze associations between EV71 vaccination quantity and rate and HFMD transmissibility. The epidemic prevention threshold, represented by required vaccination numbers and rates, was also estimated. Results: Vaccinating every 100,000 children ≤ 5 years could lead to a decrease in the R_t of EV71-associated HFMD by 14.44% (95%CI: 6.76%, 21.42%). Additionally, a positive correlation was observed between vaccinations among children ≤ 5 years old (per 100,000) and the increased transmissibility of other HFMD types (caused by enteroviruses other than EV71 and CA16) at 1.82% (95%CI: 0.80%, 2.84%). It was estimated that an additional 362,381 vaccinations, corresponding to increased vaccine coverage to 54.51% among children ≤ 5 years could effectively prevent EV71 epidemics in Zhejiang. Conclusions: Our findings highlight the importance of enhancing EV71 vaccine coverage for controlling the epidemic of EV71-HFMD and assisting government officials in developing strategies to prevent HFMD.

Chronic obstructive pulmonary disease (COPD) is a leading global cause of mortality, with ambient fine particulate matter (PM_2.5) recognized as a key environmental risk factor. However, the circulating proteomic alterations that may underlie the association between long-term PM_2.5 exposure and incident COPD remain incompletely characterized. We included 48,219 participants from the UK Biobank. Baseline plasma proteins were measured using the Olink Explore 3072 platform, and PM_2.5 concentrations were assigned using the ESCAPE land-use regression model. The PM_2.5-protein associations were estimated using multivariable linear regression. An elastic net model was used to construct a PM_2.5-related proteomic score. Cox proportional hazards models were then applied to evaluate the associations of PM_2.5 and PM_2.5-related proteomic score with incident COPD. Statistical mediation, pathway enrichment, protein-protein interaction, and druggability analyses were further performed. Over a median follow-up of 12.6 years, 1955 participants developed COPD. We identified 1629 proteins associated with PM_2.5 exposure and 1185 proteins associated with incident COPD. Among proteins associated with both PM_2.5 exposure and incident COPD, 500 showed evidence consistent with statistical mediation in exploratory analyses. The largest estimated statistical mediation proportions were observed for PLAUR (24.7%), GDF15 (17.4%), and MMP12 (16.3%). Enrichment analyses highlighted inflammatory and stress-response pathways, and protein-protein interaction analysis identified IL1B, TGFB1, and CXCL8 as network hubs. Database screening and molecular docking further prioritized PLAUR, MMP12, and CXCL8 as potentially druggable candidate proteins for future experimental evaluation. Long-term PM_2.5 exposure was associated with widespread plasma proteomic alterations, and a subset of proteins showed evidence consistent with statistical mediation of the PM_2.5-COPD association. These systems-level findings provide pathway-level biological plausibility and prioritize candidate biomarkers and potentially druggable proteins for external replication, mechanistic validation, and future translational research.

Cholera outbreaks are prevalent in coastal regions, where hydroclimatic factors play a critical role. However, evidence on their associations with different genotypes remains limited, and global projection remains lacking. We compiled cholera data from EnteroBase and WHO weekly reports covering 110 coastal countries from 1980 to 2022. A generalized additive model was used to examine the associations between hydroclimatic factors and different cholera serotypes and genotypes. We further projected future cholera occurrences for each coastal country under three climate change scenarios from 2025 to 2100. During the study period, Wave 3 of O1 replaced Wave 1 as the predominant genotype of cholera, while cholera O139 remained at low levels and only occurred in Asia. At the country–year level, each 1 °C increase in sea surface temperature (SST) was significantly associated with cholera occurrence (OR: 1.032, 95% CI: 1.023 to 1.040) and Wave 3 of O1 (OR: 1.149, 95% CI: 1.097 to 1.203). Drainage density (m/km²) and coastline ratio (%) were positively related to cholera, with ORs of 1.067 (95% CI: 1.046 to 1.087) and 1.022 (95% CI: 1.019 to 1.027). For future projections, five trend patterns were identified under different emission scenarios, with most countries showing increased cholera risk due to global hydroclimatic changes, peaking under the SSP585 scenario. Our findings reveal associations between hydroclimatic factors and different cholera genotypes and project future cholera risk across coastal countries, thereby providing evidence to inform genotype-specific surveillance and targeted prevention strategies at the global scale.

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